Instructions to use p1atdev/plat-diffusion with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use p1atdev/plat-diffusion with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("p1atdev/plat-diffusion", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps
- Draw Things
- DiffusionBee
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README.md
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license: creativeml-openrail-m
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inference: true
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thumbnail: https://
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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[kl-f8-anime2.ckpt](https://huggingface.co/hakurei/waifu-diffusion-v1-4/blob/main/vae/kl-f8-anime2.ckpt) is recommended for VAE.
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### Recomended Negative Prompt
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license: creativeml-openrail-m
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inference: true
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thumbnail: https://s3.amazonaws.com/moonup/production/uploads/1674263031698-6305db1fcfbde33ef7d480ff.png
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tags:
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- stable-diffusion
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- stable-diffusion-diffusers
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[kl-f8-anime2.ckpt](https://huggingface.co/hakurei/waifu-diffusion-v1-4/blob/main/vae/kl-f8-anime2.ckpt) is recommended for VAE.
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### Recomended Negative Prompt
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